Unravelling the Complexity: Understanding the Challenges of Reinforcement Learning
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Science & Engineering | India | Volume 13 Issue 3, March 2024 | Popularity: 4.8 / 10


     

Unravelling the Complexity: Understanding the Challenges of Reinforcement Learning

Brahmaleen Kaur Sidhu


Abstract: After an extensive research and exploration of supervised, unsupervised and semi-supervised machine learning algorithms, researchers across the numerous application domains of machine learning are now looking to implement reinforcement learning techniques as they promise a realization of more human-like intelligence in machines. This paper presents a comprehensive body of knowledge about the complexities and challenges that researchers might face while developing reinforcement learning models as solutions for real-life problems. Also, some recommendations have been made in order to assist effective implementation of reinforcement learning algorithms.


Keywords: computational complexity, environment specification, exploration-exploitation, reinforcement learning, safeRL, sample efficiency


Edition: Volume 13 Issue 3, March 2024


Pages: 233 - 239


DOI: https://www.doi.org/10.21275/SR24304190409


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Brahmaleen Kaur Sidhu, "Unravelling the Complexity: Understanding the Challenges of Reinforcement Learning", International Journal of Science and Research (IJSR), Volume 13 Issue 3, March 2024, pp. 233-239, https://www.ijsr.net/getabstract.php?paperid=SR24304190409, DOI: https://www.doi.org/10.21275/SR24304190409

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